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Report: Big data to help banks identify, avoid fraudulent declines

Big DataA recent report released by William Mills Agency, a public relations and marketing firm for the financial industry, said leveraging big data may help banks better identify and detect fraudulent transactions.

While banks have collected basic customer information for years, banks now also have access to unstructured data from online chats, their social media sites and third parties.

“The threat continues to increase, meaning that all financial services companies have to use a variety of tools to fight it,” the report said. “The more data a bank has and the more timely it receives the information, the quicker it can determine if there if there is a fraudulent transaction or pattern of fraud. The quicker the recognition, the quicker future fraudulent transactions can be stopped.”

Bob Meara, a senior analyst at Celent, said in the report, however, that big data has a “very nascent infrastructure,” pointing to the numerous analytics applications available to financial institutions.

Data from Celent showed only 38 percent of banks are deploying or expanding big data implementation programs, but the report said banks that successfully deploy big data strategies do have a number of advantages.

Steve Ramirez, the CEO of data company Beyond the Arc, said in the report that banks are able to look over data to find, for example, a high number of rejected transactions at a specific ATM, which could indicate a problem that may have never come to light with less information.

The report said big data also provides banks with an overview of customer interactions across various points-of-contact, enabling the institution to find and address potential glitches and underutilized resources.

Additionally, the report said banks will be able to target consumers for offers based on data revealed by social media, such as a promotion, birth of a child or a marriage, which can change financial needs in a way that is not immediately apparent to the bank.

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